Efficient compression of audio information reduces both the memory capacity requirements for storing the audio information, and the communication bandwidth needed for transmission of the information. To enable this compression, various audio encoding schemes, such as the ubiquitous Motion Picture Experts Group 1 (MPEG-1) Audio Layer 3 (MP3) format and the newer Advanced Audio Coding (AAC) standard, employ at least one psychoacoustic model (PAM), which essentially describes the limitations of the human ear in receiving and processing audio information. For example, the human audio system exhibits an acoustic masking principle in both the frequency domain (in which audio at a particular frequency masks audio at nearby frequencies below certain volume levels) and the time domain (in which an audio tone of a particular frequency masks that same tone for some time period after removal). Audio encoding schemes providing compression take advantage of these acoustic masking principles by removing those portions of the original audio information that would be masked by the human audio system.
To determine which portions of the original audio signal to remove, the audio encoding system typically processes the original signal to generate a masking threshold, so that audio signals lying beneath that threshold may be eliminated without a noticeable loss of audio fidelity. Such processing is quite computationally-intensive, making real-time encoding of audio signals difficult. Further, performing such computations is typically laborious and time-consuming for consumer electronics devices, many of which employ fixed-point digital signal processors (DSPs) not specifically designed for such intense processing.